Meta’s new personal AI agent Muse is moving from a clever demonstration toward something much more consequential: software that can browse the web, use connected services, send emails, book appointments and make purchases on a user’s behalf. But barely two weeks after its September 8 launch, Muse has already run into two of the hardest problems facing agentic AI: who gets to control an agent’s access to the internet, and how much trust users should place in software with broad permissions.
On September 20, Amazon blocked Muse from shopping on Amazon.com, saying Meta’s agent was an unauthorized automated tool that violated Amazon’s conditions of use. A day later, security researchers disclosed a serious macOS vulnerability that could allow an attacker with local access to hijack Muse; Meta subsequently released a hotfix. At the same time, Meta is expanding Muse’s ambitions, announcing at Meta Connect 2026 that the agent will eventually work through its AI glasses and is being brought to Mac for longer-running computer tasks.
Muse Is Not Just Another Chatbot
Meta introduced Muse as a personal AI agent, rather than a conventional question-and-answer assistant. Its purpose is to take a goal, make a plan and carry out multiple steps with less intervention from the user.
For example, Meta says Muse can open a browser, fill out forms, send an email, book travel and work on tasks after the user has closed the app. It can also remember information a user has previously shared and use that context later. For purchases, Meta designed Muse to ask for approval at sensitive moments and uses Stripe’s Link wallet to create one-time-use payment cards.
The technical foundation is a dedicated Muse Secure VM. Meta says every agent operates in an isolated virtual computer containing the agent and the user’s connected data. A separate security component called Sentinel is supposed to approve Muse’s internet access, while users choose which services the agent can connect to and what permissions it receives.
That architecture matters because an AI that can only generate text has a limited ability to cause real-world damage. An agent that can browse, log in, purchase goods, send messages or manipulate files has a much larger blast radius. The industry is therefore moving from the question “Can the model reason?” toward a harder one: What should the model be allowed to do?
Why Amazon Blocked Muse
Amazon’s decision is an important early test of that question.
According to Reuters and reporting by TechCrunch, Amazon began blocking Muse after Meta declined a request to remove the agent from the shopping experience. Amazon said third-party shopping agents should operate openly and respect a service provider’s decision about whether to participate.
The disagreement is bigger than one shopping site. Meta’s position is that Muse should be able to interact with websites in much the same way a person does when no dedicated API is available. Amazon, meanwhile, controls the rules of its own platform and has argued that third-party agents should identify themselves and obtain permission before acting on behalf of customers.
This creates a potentially important fault line for the emerging agentic web. If AI agents become the interface through which people search, compare and buy products, websites could lose some control over how their services are accessed, how recommendations are displayed and how transactions are initiated.
Shopify is taking the opposite approach. It has announced integrations designed to make agentic commerce easier for merchants, showing that the next phase of online shopping may not be about whether AI agents exist, but which platforms choose to welcome them.
A Security Problem Arrived at the Same Time
The Amazon dispute would already be significant. The security issue makes it more consequential.
Security researcher Patrick Wardle found a vulnerability in Muse’s macOS application that could allow a malicious process already running on a Mac to manipulate the agent. Ars Technica reported that the flaw could be used to redirect Muse’s transcription processing and ultimately gain control over actions performed by the agent. Meta released a hotfix after the vulnerability was reported.
There is an important limitation: this was not described as a simple remote attack against an unsuspecting Muse user. The attacker needed code or another foothold on the victim’s machine. Meta has therefore characterised the practical risk as limited. But the incident illustrates why agent security is different from ordinary chatbot security.
If an attacker compromises a conventional chatbot session, they may obtain information or manipulate a conversation. If an attacker compromises an agent that has access to email, shopping, files and other connected services, the consequences can extend into the user’s real digital life.
Meta Is Expanding Muse Beyond the Phone
Despite the early friction, Meta is accelerating rather than slowing its Muse strategy.
At Meta Connect 2026 on September 23, the company announced that Muse is being integrated with its AI glasses. Meta says users will eventually be able to ask the agent to guide workouts, log meals, provide nutrition information, book appointments or help purchase products without reaching for a phone.
Meta is also bringing Muse computer-use capabilities to Mac, allowing the agent to work across desktop applications while the user is away. The company is developing an email address for Muse and expanding integrations with services including Shopify, Stripe, PayPal, GitHub, Notion, Expedia and other partners.
The scale is already attracting attention. Reuters reported on September 23 that Muse had surpassed 2.5 million downloads and had overtaken ChatGPT in the free-app charts in the United States and Canada.
What This Means for Indian Users
There is an important caveat for India: Muse is not yet an officially launched consumer product in India. Meta’s September 8 announcement says the initial rollout is in the United States on iOS, Android and the web, with AI-glasses support coming later.
That does not make the development irrelevant to Indian users. India is one of the world’s largest smartphone and internet markets, and agentic features are likely to become part of the broader competition between Meta, Google, OpenAI, Microsoft and other AI companies. The eventual Indian version will face a particularly complex environment of UPI payments, local commerce platforms, multilingual users and services that may or may not expose APIs for AI agents.
For Indian developers and businesses, the bigger lesson is already visible: building an AI agent is only half the problem. The other half is building permission systems, identity standards, audit trails and commercial agreements that let agents operate safely across services they do not control.
The Bigger Fight Is Over the Agentic Web
Muse’s first two weeks offer a useful preview of where consumer AI is heading. The technology is shifting from generating answers to taking actions. That can make AI dramatically more useful, but it also means the boundaries between an AI company, a website and a user become much less clear.
Amazon’s block shows that websites may not automatically accept AI agents as legitimate users. The Muse security flaw shows that giving an agent powerful permissions raises the cost of mistakes and vulnerabilities. And Meta’s rapid expansion into shopping, desktop computing and glasses shows that the industry is unlikely to wait for every governance question to be solved before pushing forward.
For users, the practical rule is simple: treat an AI agent with access to your accounts more like a powerful piece of software than a chatbot. Review permissions, keep sensitive accounts disconnected unless necessary, approve transactions carefully and install security updates promptly.
The most important question about Muse is no longer whether it can shop for you. It is whether the internet is ready to let AI agents become customers in their own right.
